Experimental Study and Modeling of Automatic Home Energy Management System Using AI
| dc.contributor.author | Piyanut Pranee | |
| dc.contributor.author | Nirudh Jirasuwankul | |
| dc.date.accessioned | 2026-05-08T19:20:17Z | |
| dc.date.issued | 2021-10-20 | |
| dc.description.abstract | This paper proposes an experimental study and modeling of Fuzzy logic based-AI for home energy management system. The management model has been designed for home in the subtropical climate zone-like, i.e., Thailand, which having yearly and monthly average temperature of 28°c and 30–38°c in the hottest season respectively. The studied system model comprises of the grid-connected load of home appliances, air conditioner, type-1 EV charger and solar rooftop PV supply. The objective of energy management is to minimize grid power consuming as well as maximizing solar PV utilization with 24-hour load profile, principally running of air conditioner and EV charging load. By testing the proposed management system comparatively to the generic system without managing scheme, energy saving of 43.90% can be achieved under the same operating and environmental conditions. Those are illustrated by the simulation results. | |
| dc.identifier.doi | 10.1109/icpei52436.2021.9690647 | |
| dc.identifier.uri | https://dspace.kmitl.ac.th/handle/123456789/17451 | |
| dc.subject | Smart Grid Energy Management | |
| dc.subject | IoT-based Smart Home Systems | |
| dc.subject | Microgrid Control and Optimization | |
| dc.title | Experimental Study and Modeling of Automatic Home Energy Management System Using AI | |
| dc.type | Article |